data_analysis.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data Analysis"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Import dataset\n",
    "* IMDB movie review dataset: https://www.kaggle.com/lakshmi25npathi/imdb-dataset-of-50k-movie-reviews"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "movie_reviews = pd.read_csv(\"data/IMDB_Dataset.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analyze the dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check for NULL value"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie_reviews.isnull().values.any()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check the structure"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(50000, 2)"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie_reviews.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>review</th>\n",
       "      <th>sentiment</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>One of the other reviewers has mentioned that ...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>A wonderful little production. &lt;br /&gt;&lt;br /&gt;The...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>I thought this was a wonderful way to spend ti...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Basically there's a family where a little boy ...</td>\n",
       "      <td>negative</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Petter Mattei's \"Love in the Time of Money\" is...</td>\n",
       "      <td>positive</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                              review sentiment\n",
       "0  One of the other reviewers has mentioned that ...  positive\n",
       "1  A wonderful little production. <br /><br />The...  positive\n",
       "2  I thought this was a wonderful way to spend ti...  positive\n",
       "3  Basically there's a family where a little boy ...  negative\n",
       "4  Petter Mattei's \"Love in the Time of Money\" is...  positive"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "movie_reviews.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Check the distribution of positive and negative sentiments in the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x115870410>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "sns.countplot(x='sentiment', data=movie_reviews)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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    "version": 3
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   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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  }
 },
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}